Methods and apparatus for truncation compensation

Patent holder (s):

GE Medical Systems Global Technology Company, LLC of Waukesha, Wisconsin, United States of America (US).

Registered: 06.04.2004 IE 2004/06

Date:

27.09.2005

Issued:

01.12.2005 IE 2005/12 © Inventor (s):

Jiang Hsieh of Brookfield, Wisconsin (US) Robert H. Armstrong of Waukesha, Wisconsin (US)

Peter Joseph Arduini of Wauwatosa, Wisconsin (US)

Robert F. Senzig of Germantown, Wisconsin (US) (74) Authorized representative:

Drs. F. Barendregt et al. At 2280 GE Rijswijk.

© Truncation Compensation Methods and Devices.

NL C 1024447 (© A method includes amplifying partially sampled field of view (76) data using fully sampled field of view (60) data by using an imaging device (10), which is a radiation source (14), a radiation responsive detector (18) positioned to receive radiation emitted from the source; and a computer (36) operatively connected to the radiation source and detector, adapted to: receive data from an object CT scan, the data containing fully sampled field of view 60) data and partially sampled field of view (76) data ; amplify the received partially sampled visual field data using the fully sampled visual field data; and reconstruct an image of the object using the fully sampled visual field data and the amplified partially sampled visual field data.

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The content of this patent is in accordance with the original filed description with claim (s) and any drawings.

The Netherlands Patent Office is the Office for Industrial Property, an agency of the Ministry of

Economics

Short designation: Methods and devices for truncation compensation.

The invention generally relates to methods and devices for computed tomographic (CT) image reconstruction and more particularly to methods and devices for a truncation compensation scheme

Under some scanning conditions, parts of a patient may protrude beyond the area covered by a detector, which may lead to image artifacts and an incomplete representation of the imaged object. Some known methods have been published, which address artifact reduction, but not imaging the portion of the patient outside the visual field (FOV). However, it is desirable to image the part of the patient that protrudes beyond the FOV.

In one aspect, a method is provided. The method includes amplifying partially sampled visual field data using fully sampled visual field data.

In another aspect, an imaging device is provided. The imaging device includes a radiation source, a radiation responsive detector positioned to receive radiation emitted from the source, and a computer operatively connected to the radiation source and the detector. The computer is arranged to receive data from a Computer Tomography (CT) scan of an object, the data containing fully sampled visual field data and partially sampled visual field data. The computer is further arranged to amplify the received partially sampled visual field data using the fully sampled visual field data, and reconstruct an image of the object using the fully sampled visual field data and the amplified partially sampled visual field data.

In a further aspect, a computer readable medium is provided, which medium is encoded with a program arranged to instruct a computer to amplify partially sampled visual field data and to reconstruct an image using the fully sampled visual field data and the amplified partially sampled visual field data.

Fig. 1 is an illustrative view of a CT imaging system embodiment.

Fig. 2 is a block diagram of the system shown in FIG. 1.

Fig. 3 shows truncation artifacts.

Fig. 4 is a graph showing a total attenuation integrated across all channels as a function of the projection angle for a breast phantom.

Fig. 5 is an illustration of truncation in a clinical setting.

Fig. 6 is a graph illustrating the effect of truncated projection on total attenuation.

Fig. 7 illustrates estimate of slopes and boundaries.

Fig. 8 is an illustration of a fitted water cylinder for truncated projection.

Fig. 9 is an illustration of a projection extension tuned by means of the expected total attenuation.

Fig. 10 shows a number of images.

Provided truncation compensation methods and devices for extended field of view in computed tomography systems. As explained in detail below, in one aspect, a method is based at least in part on the property that for parallel sampling geometry, the total amount of attenuation integrated across all channels is independent of the projection angle. The devices and methods are shown with reference to the figures, in which like reference numerals indicate like elements in all figures. Such figures are intended to be illustrative rather than limiting and are incorporated herein to facilitate explanation of an exemplary embodiment of the devices and methods of the invention.

In some known CT imaging system configurations, a radiation source projects a fan-shaped beam collimated to lie within an XY plane of a Cartesian coordinate system and generally referred to as an imaging plane. The radiation beam passes through an object to be imaged, such as a patient. After being attenuated by the object, the beam strikes a matrix of radiation detectors. The intensity of the attenuated radiation beam received on the detector array is dependent on the attenuation of a radiation beam caused by the object.

Each detector element of the matrix produces a separate electrical signal, which is a measurement of the beam attenuation in the detector location. The attenuation measurements from all detectors are collected separately to produce a transmission profile.

In third-generation CT systems, the radiation source and detector array are rotated with a portal in the imaging plane and around the object to be imaged, so that an angle at which the radiation beam intersects the object changes constantly. A group of radiation attenuation measurements, ie projection data, from the detector array at one gantry angle, is referred to as a view. A scan of the object contains a series of views taken at different gantry or viewing angles during one revolution of the radiation source and detector.

In an axial scan, the projection data is processed to reconstruct an image corresponding to a two-dimensional slice of the object. One method of reconstructing an image from a series of projection data is referred to in the art as the filtered back projection technique. This process converts the attenuation measurements from a scan into integers, called CT numbers or Houndsfield units, which are used to control the brightness of a corresponding pixel on a display.

To reduce the total scan time, a helical scan can be performed. To perform a helical scan, the patient is moved while collecting the data for the prescribed number of slices. Such a system generates a single helix from a fan beam helical scan. The helix mapped by the fan beam provides projection data from which images can be reconstructed in any prescribed slice.

As used herein, a singular and preceded by the word an element or step should not be construed as plural forms thereof unless such exclusion is explicitly stated. Moreover, references to one embodiment of the present invention are not intended to be construed as the existence of additional embodiments, which also include the stated features, only.

As used herein, the phrase reconstructing an image is not intended to exclude embodiments of the present invention in which data representing an image is generated but not a visible image. Therefore, as used herein, the term image broadly refers to visible images and data representing a visible image.

However, many embodiments (or are arranged to generate) generate at least one visible image.

Fig. 1 is an illustrated view of a CT imaging system 10. FIG. 2 is a block diagram of the system shown in FIG. 1

10. In the exemplary embodiment, a computed tomography (CT) imaging system 10 is shown, which system includes a portal 12 representative of a third-generation CT imaging system. Portal 12 has a radiation source 14, which projects a cone 15 beam 16 of X-rays onto a detector array 18 on the opposite side of portal 12.

The detector array 18 is constituted by a plurality of detector rows (not shown), which rows include a plurality of detector elements 20, which elements together perceive the projected X-ray beams 20 passing through an object, such as a medical patient 22. Each detector element 20 produces an electrical signal representing the intensity of an incident radiation beam and thereby the attenuation of the beam as it passes through the object or patient 22. An imaging system 10 with a multiple slice detector 18 is capable of providing a number of images representative of a volume of the object 22. Each image of the number of images corresponds to a separate slice of the volume. The thickness or aperture of the slice depends on the thickness of the detector rows.

During a scan for collecting radiation projection data, the gantry 12 and the components mounted thereon rotate about a center of rotation 24. FIG. 2 shows only a single row of detector elements 20 (ie a detector row). However, a multiple slice detector array 18 includes a plurality of parallel detector rows of detector elements 20, so that detection data corresponding to a number of quasi-parallel or parallel slices can be simultaneously collected during a scan.

The rotation of the portal 12 and the operation of the radiation source 14 are controlled by a control mechanism 26 of the CT system δΙΟ. The control mechanism 26 includes a radiation controller 297 that provides energy and timing signals to the radiation source 14, and a portal motor controller 30, which controls the rotational speed and position of the portal 12. A data collection system (DAS) 32 in the control mechanism 26 samples the analog data from the detector elements 20 and converts the data into digital signals for subsequent processing. An image reconstruction element 34 receives the sampled and digitized radiation data from DAS 32 and performs a high-speed image reconstruction. The reconstructed image is supplied as an input into a computer 36, which stores the image in a mass storage device 38.

The computer 36 also receives commands and scan parameters from an operator through a console 40, which has a keyboard. An associated cathode ray tube display 42 allows the operator to observe the reconstructed image and other data from computer 36. The commands and parameters provided by the operator are used by the computer 36 to provide control signals and information to DAS 32, the radiation controller 28 and the portal engine controller 30. In addition, the computer 36 controls a table 20 motor controller 34, which controller controls a motorized table 46 to position a patient 22 in the portal 12. In particular, the table 46 moves parts of the patient 22 through a portal opening 48.

In one embodiment, the computer 36 includes a device 50, for example, a flexible disk drive or CD-ROM drive, for reading instructions and / or data from a computer-readable medium 52, such as a flexible disk or CD-ROM. In another embodiment, the computer 36 executes stored instructions from the manufacturer installed software (not shown). Generally, a processor in at least one of DAS 32, reconstruction element 34 and computer 36, shown in Figure 2, is programmed to perform the processes described below. The method is of course not limited to implementation in the CT system 10 and the method can be used in conjunction with many other types and variations of imaging systems. In one embodiment, the computer 36 is programmed to perform functions described herein, and accordingly the term computer used herein is not limited to only those integrated circuits referred to in the art as computers, but broadly refers to computers, processors , microcontrollers, microcomputers, programmable logic controllers, application specific integrated circuits and other programmable circuits. While the methods described herein have been described in a medical environment, it is contemplated that the benefits of the invention also extend to non-medical imaging systems, such as those typically used in an industrial or transportation environment, such as, for example, but not limited to that, a CT baggage scanning system for an airport or other transportation center.

Under some scanning conditions, parts of the patient protrude beyond the area covered by the detector 19, which can lead to image artifacts and an incomplete representation of the imaged object. The X-ray tube and detector 18 are held together rigidly on a frame rotating about the patient aperture. During rotation, measurements are taken continuously within a fully sampled field of view 60. The attenuation of X-rays crossing regions of the object 22 positioned outside the fully sampled field of view 76 is measured in a limited range of rotation angles and this area is referred to as the partially sampled field of view. In other words, portions that are within the fully sampled field of view 76 are positioned within the impeller 16 so that measurements are available at all gantry angles, and the data collected is defined as fully sampled field of view data. Other parts are located at some angles within the impeller 16, but at other angles, they will be outside the impeller 16, and the data collected with respect to these parts is defined as partially sampled visual field data.

Some known methods have been published which address arte fact reduction, but not imaging the part of the patient outside the visual field (FOV). However, it is desirable to use the part of the patient outside the visual field (FOV). the FOV, which is useful in many areas, including oncology, spin angiography, fused imaging systems, and in economic CT scanners. Current equipment of known multi-slice CT scanners limits the reconstruction field of view (FOV) to about 50 centimeters (cm). While this is sufficient for most clinical applications, it is desirable to expand the FOV to display objects outside of this FOV. This can be particularly advantageous

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for applications such as oncology or CT / PET. A large FOV is required for oncology applications. This is mainly due to the fact that for radiation treatment planning, the patient's limbs are often positioned outside the scan FOV for better tumor positioning. The well-known CT reconstruction algorithms ignore the truncated projections and produce images with serious artifacts. These artifacts can affect an accurate attenuation path for treatment planning. One phantom example is shown in Figure 3. For fused imaging systems, such as CT / PET (computed tomography / positron emission tomography), the FOV of the PET system may not fit the existing CT design. It is desirable to have a consistent FOV between the CT system and the other imaging system (CT / PET, CT / NOC (CT / Nuclear) or CT / MR (CT / Magnetic Resonance). This correction can be used to measure the FOV adjust to match This allows for a better attenuation correction for PET, which describes an algorithmic approach to increase the reconstruction FOV beyond the FOV bounded by the detector equipment. This correction algorithm can be applied to various reconstruction algorithms including, but not limited to, full scan, half scan / segment, helical scan and the heart sector based algorithms. In addition, system 10 is arranged to apply the algorithms described herein.

Fig. 4 shows the total amount of attenuation plotted as a function of the projection angle with a parallel beam sampling geometry for a breast scan. Note that the curve is almost a horizontal line. However, this property does not exist for the fan beam sampling geometry. When the scanned object is outside the scanning field of view (FOV), this property is no longer valid. The degree of incompleteness is equal to the part of the object that is outside the projection FOV. In almost all clinical cases, the projection truncation occurs only for a portion of the projection angles, as shown in Figure 535. In this example, the projection taken at 3 o'clock position is truncated and the projection taken at 12 o'clock position is strongly truncated. Therefore, one can rely on the untruncated projections (ie, positions around 3 o'clock in Fig. 4) to estimate the amount of truncation for the truncated images (ie, positions around 12 o'clock in Fig. 5). An early step in the correction process is to execute software fan beam to parallel beam repository on the preprocessed projections. In one embodiment, this early step is the first step. This process is well known in the art and does not require any special data collection. Once the re-save is complete, the projections are integrated across all detector channels to obtain the total attenuation curve as shown in Fig. 6. Note that the decreases in the total attenuation curve correspond to images with truncation. The flat part of the curve corresponds to the images in which no object truncation occurs. Once the total amount of the object outside the FOV has been estimated, the next step is to estimate the distribution of the missing projection. In order to achieve this goal, in one embodiment the boundary reading is first calculated, p_X and p_r, as shown below in Equation 1, in the truncated projection, as shown in Fig. 7. To reduce noise, the average of m samples is used in one embodiment. It has been found empirically that m = 3 is useful in reducing noise. In other embodiments, m is greater than 1 and less than 5.

j. m 1 ®

Equation 1: Pi = - Σ Ρ &amp; ^and Pr ^{= —} Ö PÖ * LW ^mi = 1 ^mi = i where N is the number of detector channels and k is the projection image index.

In one embodiment, moreover, the slopes, Si and s_r, estimated near both ends. The slope estimate is performed by matching a first-order polynomial to n samples near the ends. It has been found empirically that n = 5 is useful. In one embodiment, n is greater than 2 and less than 8. In another embodiment, n is greater than 3 and less than 7.

Projections obtained from neighboring detector rows are used to further improve the reliability of the estimate. Since the human anatomy does not change rapidly over a short distance (a few millimeters), the boundary samples and slopes estimated from the adjacent rows typically do not vary significantly. The estimated parameters (pi, p_r, Si and s_r) can therefore be the weighted average of the values ​​calculated from different detector rows. Based on the boundary and slope information, it is estimated a location and size of a cylindrical water object that best suits the truncated projection. If we denote the attenuation coefficient of water with μ „, the radius of the cylinder with R and the distance from the center of the cylinder with X, the projection value p (x) and the slope p '(x) can be given by the following equation described.

Equation 2: p (x) = 2g_wVR² - x² and p * (x, = - = ^ ==

Fr.² - x²

Since we calculate both p (x) and p '(x) at the truncated projection boundaries, the aim is to estimate R and x, so that one adds the size and location of the cylinder to be added to the missing projection, obtains. The formulas for estimating these parameters can be described by the following equations:

Equation 3: ~ *^3l) and R_X = ^{+ x}l ^

4μ "² VW

Equation 4:

-ter) (p_r)

4μ «² and R, - = ρμ_Μ

The variables represent the approximate location and size of the cylindrical objects to be expanded from the truncated object. Once these parameters are determined, the projections used can be calculated using equation (2). The process is shown in Fig. 8.

In this example, a cylindrical water phantom was used for simplicity. In reality, other object shapes, such as an elliptical cylinder, can also be used to increase flexibility. If information about the characteristics of the scanned object is available in advance, this information can of course be used in the choice of the shape and material of the object to be added. Iterative methods can be used to estimate the missing projection data.

The estimated cylinders at both ends of the projection do not always restore the total amount of attenuation for the ge1 02444?

whole projection, since these objects are only determined from the slope and boundary samples. No part of the information derived from the overall attenuation curve (Fig. 6) is used. To ensure proper compensation for the total attenuation loss, 5 the attenuation distribution of the left side, Tj, is opposite the right side T_r, determined from the sizes of pi and p_r.

Tl =

PlT

Pl + Pr and

Tl =

Pr^T

Pl + Pr where T is the total amount of attenuation loss determined from Figure 6. If the amount of attenuation under the extended curve is insufficient to compensate for the attenuation loss, the estimated projection is stretched to meet the attenuation deficits as shown in Fig. 9. On the other hand, if the amount of attenuation under the extended curve exceeds the attenuation loss, the estimated projection is similarly compressed. In one embodiment, the calculation process is as follows. First, the ratio of the expected total attenuation (shown in equation (5), over the area under the extended projection curve (shown by the shaded area in Figure 9) is calculated. If the ratio is greater than one, the x-axis is adjusted by the ratio so that the projected initial estimate (shown by the dashed line in Fig. 9) is further expanded (shown by the solid solid line in Fig. 9). If the ratio is significantly less than one, the extended projection can be correspondingly compressed in x.

Fig. 10 shows an example of the reconstructed phantom images without and with correction. A shoulder phantom was scanned in an axial scan mode with a 4x1.25 mm detector configuration. A 15 cm plastic atom was attached to the shoulder phantom in such a way that the edge of the plastic atom is near the boundary of the 65 cm FOV. The truncated object is almost completely restored. Note that fig. 10 (a) was reconstructed with a 50 cm FOV without truncation correction (current product limit) and that Fig. 10 (b) was reconstructed with a 65 cm FOV with the correction described herein. For reference, the partial truncated phantom is shown in Fig. 10 (c).

Although the system described above and the methods described above use only the maintenance of the overall attenuation, size and slope of the boundary patch units to estimate the missing projection distribution, additional information can also be used for the estimation. For example, one will be able to use the Helgason-Ludwig condition (HL condition) for tomography to further refine the above technique. In addition, several threshold values ​​can be placed to ensure that the algorithm functions correctly under incorrect measurement conditions. For example, it will be possible to set the upper and lower limits of the stretch ratio described in Fig. 9 to avoid the condition of an increased error due to an unreliable measurement. In addition, the slope calculation of si and s_r be set to fall within a reasonable range. If it is known that the characteristic of the material of the scanned object differs significantly from water, one can also use the attenuation coefficients of the known material (instead of water) to calculate size and location calculations shown in equations (3) and (4). to be carried out.

Since the interpolated data does not have the same image quality as the data within the fully sampled FOV, it may be useful to mark the image extrapolated the FOV. In one embodiment, a delineation in a reconstructed image between regions representative of the fully sampled visual field data and the partially sampled visual field data is provided. Fig. 10 (d) shows the boundary marked by a dashed line. This can also be done with a color code or shift in the CT nuromer. Since the marker can affect the ability to see the image data, a simple way to turn the marker on and off is provided.

A user of the system 10 is enabled to enable or disable the marking.

Although the invention has been described in terms of various specific embodiments, those skilled in the art will recognize that the invention can be practiced with a modification within the scope of the claims.

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